AIMC Topic: Predictive Value of Tests
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CT morphological index provides incremental value to machine learning based CT-FFR for predicting hemodynamically significant coronary stenosis.
International journal of cardiology
Aug 15, 2018
AIMS: To study the diagnostic performance of the ratio of Duke jeopardy score (DJS) to the minimal lumen diameter (MLD) at coronary computed tomographic angiography (CCTA) and machine learning based CT-FFR for differentiating functionally significant...
Predicting Language Difficulties in Middle Childhood From Early Developmental Milestones: A Comparison of Traditional Regression and Machine Learning Techniques.
Journal of speech, language, and hearing research : JSLHR
Aug 8, 2018
PURPOSE: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) bro...
Neural Networks for Prognostication of Patients With Heart Failure.
Circulation. Heart failure
Aug 1, 2018
Background Prognostication of heart failure patients from cardiopulmonary exercise test (CPET) currently involves simplification of complex time-series data into summary indices. We hypothesized that prognostication could be improved by considering t...
Artificial intelligence can predict daily trauma volume and average acuity.
The journal of trauma and acute care surgery
Aug 1, 2018
BACKGROUND: The goal of this study was to integrate temporal and weather data in order to create an artificial neural network (ANN) to predict trauma volume, the number of emergent operative cases, and average daily acuity at a Level I trauma center.
Predicting Mortality in the Surgical Intensive Care Unit Using Artificial Intelligence and Natural Language Processing of Physician Documentation.
The American surgeon
Jul 1, 2018
The purpose of this study was to use natural language processing of physician documentation to predict mortality in patients admitted to the surgical intensive care unit (SICU). The Multiparameter Intelligent Monitoring in Intensive Care III database...
False-positive Troponin I Assay elevation due to occult Mixed Cryoglobulinemic Vasculitis.
Reviews in cardiovascular medicine
Jun 30, 2018
A 53-year-old man with active hepatitis C and cirrhosis presented with a vasculitic rash, myalgias, and fatigue, and was found to have an elevated cardiac troponin I up to 15.7 ng/mL with normal electrocardiogram, echocardiogram, and coronary angiogr...
Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.
Circulation. Cardiovascular imaging
Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Asia
Computed Tomography Angiography
Severity of Illness Index
Coronary Stenosis
Deep Learning
Fractional Flow Reserve, Myocardial
United States
Europe
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Female
Coronary Artery Disease
Humans
Coronary Vessels
Prospective Studies
Reproducibility of Results
Retrospective Studies
Aged
Male
Middle Aged
Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation.
Neuroinformatics
Apr 1, 2018
The advances in neuroimaging methods reveal that resting-state functional fMRI (rs-fMRI) connectivity measures can be potential diagnostic biomarkers for autism spectrum disorder (ASD). Recent data sharing projects help us replicating the robustness ...
Detection of tuberculosis patterns in digital photographs of chest X-ray images using Deep Learning: feasibility study.
The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
Mar 1, 2018
OBJECTIVE: To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of chest X-ray (CXR) images of tuberculosis (TB) patients.
Use of Fetal Magnetic Resonance Image Analysis and Machine Learning to Predict the Need for Postnatal Cerebrospinal Fluid Diversion in Fetal Ventriculomegaly.
JAMA pediatrics
Feb 1, 2018
IMPORTANCE: Which children with fetal ventriculomegaly, or enlargement of the cerebral ventricles in utero, will develop hydrocephalus requiring treatment after birth is unclear.
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